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Abstract

Many studies of neonates with a variety of conditions support EEG as a good prognostic indicator of outcome. However, the availability of expert neonatal EEG is very limited, available only at a relatively few specialized pediatric centers in the country. In addition, long-term monitoring of the EEG, which can provide the most accurate prognosis in neonates, is rarely used in clinical practice now because of the considerable effort required to review long-term data. This Phase I project will focus on the development of accurate and reliable signal processing methods specific for analyzing and characterizing the background EEG in neonates. The objective is to develop an automated classifier of the background neonatal EEG that will agree with assessments made by clinical experts. The eventual goal is the development of a low-cost, easy-to-use monitor that can provide long-term continuous assessments of the neonatal background EEG. Such a monitor could be a good measure of treatment success, indicating neurological improvement or decline after treatment has been given. Also, it could impact level of care decisions, especially for those neonates given poor prognoses (e.g.: severe neurological deficits, or death). PROPOSED COMMERCIAL APPLICATIONS: There is a large commercial potential for an EEG neurological assessment monitor for neonates. There are approximately 13,000 neonatal ICU beds in major medical markets worldwide. Selling monitors to just 1% of that market per year at approximately $10,000 per unit would yield annual revenues of $1.8 million.